scispace - formally typeset
Journal ArticleDOI

Tracking Suicide Risk Factors Through Twitter in the US

Reads0
Chats0
TLDR
Twitter may be a viable tool for real-time monitoring of suicide risk factors on a large scale and demonstrates that individuals who are at risk for suicide may be detected through social media.
Abstract
Background: Suicide is a leading cause of death in the United States. Social media such as Twitter is an emerging surveillance tool that may assist researchers in tracking suicide risk factors in real time. Aims: To identify suicide-related risk factors through Twitter conversations by matching on geographic suicide rates from vital statistics data. Method: At-risk tweets were filtered from the Twitter stream using keywords and phrases created from suicide risk factors. Tweets were grouped by state and departures from expectation were calculated. The values for suicide tweeters were compared against national data of actual suicide rates from the Centers for Disease Control and Prevention. Results: A total of 1,659,274 tweets were analyzed over a 3-month period with 37,717 identified as at-risk for suicide. Midwestern and western states had a higher proportion of suicide-related tweeters than expected, while the reverse was true for southern and eastern states. A strong correlation was observed between sta...

read more

Citations
More filters
Proceedings ArticleDOI

Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media

TL;DR: This paper develops a statistical methodology to infer which individuals could undergo transitions from mental health discourse to suicidal ideation, and utilizes semi-anonymous support communities on Reddit as unobtrusive data sources to infer the likelihood of these shifts.
Journal ArticleDOI

Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.

TL;DR: A layered, hierarchical model for translating raw sensor data into markers of behaviors and states related to mental health is provided, focused principally on smartphones, but also including studies of wearables, social media, and computers.
Journal ArticleDOI

Detecting suicidality on Twitter

TL;DR: This project was supported in part by funding from the NSW Mental Health Commission and the NHMRC John Cade Fellowship 1056964.
Proceedings ArticleDOI

From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses

TL;DR: A broad range of mental health conditions in Twitter data is examined by identifying self-reported statements of diagnosis and language differences between ten conditions with respect to the general population, and to each other are systematically explored.
References
More filters
Journal ArticleDOI

The measurement of observer agreement for categorical data

TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
Proceedings ArticleDOI

Predicting the Future with Social Media

TL;DR: It is shown that a simple model built from the rate at which tweets are created about particular topics can outperform market-based predictors and improve the forecasting power of social media.

Of mental health.

Journal ArticleDOI

The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic

TL;DR: The use of information embedded in the Twitter stream is examined to (1) track rapidly-evolving public sentiment with respect to H1N1 or swine flu, and (2) track and measure actual disease activity.
Journal Article

National Hospital Ambulatory Medical Care Survey: 2007 Emergency Department Summary

TL;DR: This report presents data on U.S. emergency department (ED) visits in 2007, with statistics on hospital, patient, and visit characteristics, using data from the 2007 National Hospital Ambulatory Medical Care Survey.
Related Papers (5)